A Critical Review of Crack Detection Based on Image Processing

Abstract

In order to extract meaningful observations from an image, it is essential to first convert it into a digital format and then apply a particular processing methodology. In the domain of image processing, it is a prevalent convention to consider all images as signals that are two-dimensional in nature, while utilizing conventional signal processing methodologies. The existence of surface fissures in concrete acts as an initial indication of probable structural deterioration. The utilization of image-based automated fracture identification is proposed as a viable alternative in situations where a human replacement is unavailable. This paper provides a critical review of crack detection using image processing. The scholarly literature encompasses a range of image processing techniques that can be employed for the automated identification of fractures and their respective depths. The present research involves a comprehensive examination with the objective of discerning the existing obstacles and past accomplishments within this area of investigation. A total of 24 publications related to the detection of Ato cracks have been selected for the purpose of conducting a comprehensive review. Following the review, a comprehensive analysis is performed on various image processing techniques, encompassing their respective objectives, degrees of accuracy and inaccuracy, as well as the datasets of images utilized. This study also presents future research efforts in identifying and resolving the problem of crack detection.